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Artificial Intelligence in Accelerating Drug Discovery and Development

Author(s): Anushree Tripathi*, Krishna Misra*, Richa Dhanuka and Jyoti Prakash Singh

Volume 17, Issue 1, 2023

Published on: 05 September, 2022

Page: [9 - 23] Pages: 15

DOI: 10.2174/1872208316666220802151129

Price: $65

Abstract

Drug discovery and development are critical processes that enable the treatment of wide variety of health-related problems. These are time-consuming, tedious, complicated, and costly processes. Numerous difficulties arise throughout the entire process of drug discovery, from design to testing. Corona Virus Disease 2019 (COVID-19) has recently posed a significant threat to global public health. SARS-Cov-2 and its variants are rapidly spreading in humans due to their high transmission rate. To effectively treat COVID-19, potential drugs and vaccines must be developed quickly. The advancement of artificial intelligence has shifted the focus of drug development away from traditional methods and toward bioinformatics tools. Computer-aided drug design techniques have demonstrated tremendous utility in dealing with massive amounts of biological data and developing efficient algorithms. Artificial intelligence enables more effective approaches to complex problems associated with drug discovery and development through the use of machine learning. Artificial intelligence-based technologies improve the pharmaceutical industry's ability to discover effective drugs. This review summarizes significant challenges encountered during the drug discovery and development processes, as well as the applications of artificial intelligence-based methods to overcome those obstacles in order to provide effective solutions to health problems. This may provide additional insight into the mechanism of action, resulting in the development of vaccines and potent substitutes for repurposed drugs that can be used to treat not only COVID-19 but also other ailments.

Keywords: Drug design, bioinformatics, artificial intelligence (AI), pharmaceutical applications, COVID-19, machine learning (ML).

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